Dataset Information

MicroRNA-17 as a promising diagnostic biomarker of gastric cancer: An investigation combining TCGA, GEO, meta-analysis, and bioinformatics.

ABSTRACT: Integrated studies of accumulated data can be performed to obtain more reliable information and more feasible measures for investigating potential diagnostic biomarkers of gastric cancer (GC) and to explore related molecular mechanisms. This study aimed to identify microRNAs involved in GC by integrating data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus. Through our analysis, we identified hsa-miR-17 (miR-17) as a suitable candidate. We performed a meta-analysis of published studies and analyzed clinical data from TCGA to evaluate the clinical significance and diagnostic value of miR-17 in GC. miR-17 was found to be upregulated in GC tissues and exhibited a favorable value in diagnosing GC. In addition, we predicted that 288 target genes of miR-17 participate in GC-related pathways. Enrichment of Kyoto Encyclopedia of Genes and Genomes pathway, Gene Ontology analysis, and protein-protein interaction analysis of the 288 target genes of miR-17 were also performed. Through this study, we identified possible core pathways and genes that may play an important role in GC. The possible core pathways include the cAMP, phosphoinositide-3-kinase-Akt, Rap1, and mitogen-activated protein kinase signaling pathways. miR-17 may be involved in several biological processes, including DNA template transcription, the regulation of transcription from RNA polymerase II promoters, and cell adhesion. In addition, cellular components (such as cytoplasm and plasma membrane) and molecular functions (such as protein binding and metal ion binding) also seemed to be regulated by miR-17.

SUBMITTER: Hu G

PROVIDER: S-EPMC6120248 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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MicroRNA-17 as a promising diagnostic biomarker of gastric cancer: An investigation combining TCGA, GEO, meta-analysis, and bioinformatics.

Hu GaoFeng G Lv QianWen Q Yan JiaXiu J Chen LiJun L Du Juan J Zhao Ke K Xu Wei W

FEBS open bio 20180830 9

Integrated studies of accumulated data can be performed to obtain more reliable information and more feasible measures for investigating potential diagnostic biomarkers of gastric cancer (GC) and to explore related molecular mechanisms. This study aimed to identify microRNAs involved in GC by integrating data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus. Through our analysis, we identified hsa-miR-17 (miR-17) as a suitable candidate. We performed a meta-analysis of published s ...[more]

PMID: 30186751

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Dataset Information

MicroRNA-17 as a promising diagnostic biomarker of gastric cancer: An investigation combining TCGA, GEO, meta-analysis, and bioinformatics.

Publications

MicroRNA-17 as a promising diagnostic biomarker of gastric cancer: An investigation combining TCGA, GEO, meta-analysis, and bioinformatics.

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